Fault prediction framework using temporal data mining
First Claim
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1. A vehicle fault diagnosis and prognosis system, comprising:
- a computing platform on the vehicle configured to receive a fault classifier from a remote server, the computing platform tangibly embodying computer-executable instructions for;
evaluating local data sequences received from a vehicle control network; and
applying the classifier to the local data sequences, wherein the classifier is configured to determine if the local data sequences define a pattern associated with a particular fault where the classifier is trained by comparing data sequences from a first population of vehicles to repair data from a second population of vehicles.
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Abstract
A vehicle fault diagnosis and prognosis system includes a computing platform configured to receive a classifier from a remote server, the computing platform tangibly embodying computer-executable instructions for evaluating data sequences received from a vehicle control network and applying the classifier to the data sequences, wherein the classifier is configured to determine if the data sequences define a pattern that is associated with a particular fault.
32 Citations
21 Claims
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1. A vehicle fault diagnosis and prognosis system, comprising:
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a computing platform on the vehicle configured to receive a fault classifier from a remote server, the computing platform tangibly embodying computer-executable instructions for; evaluating local data sequences received from a vehicle control network; and applying the classifier to the local data sequences, wherein the classifier is configured to determine if the local data sequences define a pattern associated with a particular fault where the classifier is trained by comparing data sequences from a first population of vehicles to repair data from a second population of vehicles. - View Dependent Claims (2, 3, 4)
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5. A method for fault diagnosis and prognosis, comprising:
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extracting data sequences from a first population of vehicles; applying a temporal data mining application to the data sequences extracted from the first population of vehicles to detect patterns in the data sequences; retrieving repair data related to a second population of vehicles; comparing the data sequences to the repair data to identify data sequences that are related to a particular failure mode; applying a clustering algorithm to create clusters of data sequences related to the particular failure mode using the identified data sequences that are related to the particular failure mode; training a fault prediction classifier to learn the particular failure modes associated with each cluster so the fault prediction classifier can identify the data sequences that lead to particular failure modes, said fault prediction classifier using a neural network, a support vector machine and a decision tree; sending the fault classifier to a computing platform on a vehicle; and receiving the fault classifier in the computing platform and the computing platform executing instructions for; evaluating data sequences received from a vehicle control network; and applying the classifier to the data sequences, wherein the classifier is configured to determine if the data sequences define a pattern associated with a particular fault. - View Dependent Claims (6, 7, 8, 9, 10)
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11. A computer-readable medium tangibly embodying computer-executable instructions for:
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extracting data sequences from a first population of vehicles; applying a temporal data mining application to the data sequences extracted from the first population of vehicles to detect patterns in the data sequences; retrieving repair data related to a second population of vehicles; comparing the data sequences to the repair data to identify data sequences that are related to a failure mode; applying a clustering algorithm to create clusters of data sequences related to the failure mode using the identified data sequences that are related to the failure mode; and training a fault prediction classifier to learn the failure modes associated with each cluster so the fault prediction classifier can identify the data sequences that lead to failure modes, said fault prediction classifier using a neural network. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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Specification